Latent variable models for multivariate longitudinal ordinal responses

Abstract

The paper proposes a full information maximum likelihood estimation method for modelling multivariate longitudinal ordinal variables. Two latent variable models are proposed that account for dependencies among items v/ithin time and between time. One model fits item-specific random effects which account for the between time points correlations and the second model uses a common fector. The relationships between the time-dependent latent variables are modelled with a non-stationary autoregressive model. The proposed models are fitted to a real data set.